LIDAR-based geometric reconstruction of boreal type forest stands at single tree level for forest and wildland fire management

Morsdorf, Felix; Meier, Erich; Kötz, Benjamin; Itten, K.I.; Dobbertin, Matthias; Allgöwer, Britta

doi:10.1016/j.rse.2004.05.013

Cited by 338 publications

(207 citation statements)

References 15 publications

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“…The RMSE was relatively large, 2.18 m, but this value was similar to that found by Hollaus et al (2006) and might be explained by operator based errors made in the field measurements. Subsequently, the quality of the LiDAR derived CHM was found to be equivalent to that noted by previous contributors (Akay et al, 2012;Clark et al, 2004;Koukoulas and Blackburn, 2005;Morsdorf et al, 2004).…”

Section: Validation Resultssupporting

confidence: 67%

LiDAR derived ecological integrity indicators for riparian zones: Application to the Houille river in Southern Belgium/Northern France

Michez¹,

Piégay²,

Toromanoff³

et al. 2013

Ecological Indicators

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a b s t r a c tRiparian zones are central landscape features providing several ecosystem services and are exceptionally rich in biodiversity. Despite their relatively low area coverage, riparian zones consequently represent a major concern for land and water resource managers confirmed within several European directives. These directives involve effective multi-scale monitoring to assess their conditions and their ability to carry out their functions. The objective of this research was to develop automated tools to provide from a single aerial LiDAR dataset new mapping tools and keystone riparian zone attributes assessing the ecological integrity of the riparian zone at a network scale (24 km).Different metrics were extracted from the original LiDAR point cloud, notably the Digital Terrain Model and Canopy Height Model rasters, allowing the extraction of riparian zones attributes such as the wetted channel (0.89 m; mean residual) and floodplain extents (6.02 m; mean residual). Different riparian forest characteristics were directly extracted from these layers (patch extent, overhanging character, longitudinal continuity, relative water level, mean and relative standard deviation of tree height). Within the riparian forest, the coniferous stands were distinguished from deciduous and isolated trees, with high accuracy (87.3%, Kappa index).Going further the mapping of the indicators, our study proposed an original approach to study the riparian zone attributes within different buffer width, from local scale (50 m long channel axis reach) to a network scale (ca. 2 km long reaches), using a disaggregation/re-agraggation process. This novel approach, combined to graphical presentations of the results allow natural resource managers to visualise the variation of upstream-downstream attributes and to identify priority action areas.In the case study, results showed a general decrease of the riparian forests when the river crosses built-up areas. They also highlighted the lower flooding frequency of riparian forest patches in habitats areas.Those results showed that LiDAR data can be used to extract indicators of ecological integrity of riparian zones in temperate climate zone. They will enable the assessment of the ecological integrity of riparian zones to be undertaken at the regional scale (13,000 km, completely covered by an aerial LIDAR survey in 2014).

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Section: Validation Resultssupporting

confidence: 67%

LiDAR derived ecological integrity indicators for riparian zones: Application to the Houille river in Southern Belgium/Northern France

Michez¹,

Piégay²,

Toromanoff³

et al. 2013

Ecological Indicators

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“…According to previous studies (Morsdorf et al 2004, Kandare et al 2016, the detection was less successful in stands with higher presence of deciduous species with closed crown canopy, due to their crown morphology with indistinct treetop. On the other hand, the crown projections were delineated with a very high accuracy (-2 ± 6%) and the shape of delineated crowns represented the real 2D crown projection very well.…”

Section: Accuracy Of Tree Detectionmentioning

confidence: 86%

Integration of tree allometry rules to treetops detection and tree crowns delineation using airborne lidar data

Sačkov¹,

Hlásny²,

Bucha³

et al. 2017

iForest

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Airborne laser scanning (ALS) has recently gained increasing attention in forestry, as ALS data may facilitate the efficient assessment of forest inventory attributes and ecological indicators related to forest stand structure. This paper presents a novel workflow for individual tree detection and tree crown delineation using ALS data. The developed point-based approach included several tree allometry rules on permissible tree heights and crown dimensions to increase the likelihood of detecting the actual tree profiles. The accuracy of the method was assessed in a heterogeneous forest with a complex stand structure in Slovakia (Central Europe). ALS measurements were taken using a RIEGL Q680i scanner at 700 m of height with a point density of 20 echoes per m 2 . The ground reference data included the measured positions and dimensions of 1332 trees in nine plots distributed across the region. We found that the number of individual trees detected by the algorithm using ALS data was systematically underestimated by 34 ± 15% relative to the reference data. The delineated crown coverage was underestimated by 2 ± 6% as well, but the latter difference was not statistically significant (p>0.05).

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“…Consequently, the present study recommends delineating tree crowns using DCHM data instead of optical data. In addition, several authors delineated individual trees in boreal forests with high accuracy using ALS data by the individual tree detection (ITD) algorithm [34,37,40,[70][71][72]. Although our study achieved comparable tree detection results, further research is required to study the influence of different approaches on tree delineation [73].…”

Section: Discussionmentioning

confidence: 66%

Interpretation of Forest Resources at the Individual Tree Level in Japanese Conifer Plantations Using Airborne LiDAR Data

Deng

Katoh

2016

Remote Sensing

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More than 50% of the national lands in Japan have been surveyed by airborne laser scanning (ALS) data with different point densities; and developing an effective approach to take full advantage of these ALS data for forest management has thus become an urgent topic of study. This study attempted to assess the utility of ALS data for individual tree detection and species classification in a mixed forest with a high canopy density. For comparison, two types of tree tops and tree crowns in the study area were delineated by the individual tree crown (ITC) approach using the green band of the orthophoto imagery and the digital canopy height model (DCHM) derived from the ALS data, respectively. Then, the two types of tree crowns were classified into four classes-Pinus densiflora (Pd), Chamaecyparis obtusa (Co), Larix kaempferi (Lk), and broadleaved trees (Bl)-by a crown-based classification approach using different combinations of the three orthophoto bands with intensity and slope maps as follows: RGB (red, green and blue); RGB and intensity (RGBI); RGB and slope (RGBS); and RGB, intensity and slope (RGBIS). Finally, the tree tops were annotated with species attributes from the two best-classified tree crown maps, and the number of different tree species in each compartment was counted for comparison with the field data. The results of our study suggest that the combination of RGBIS yielded greater classification accuracy than the other combinations. In the tree crown classifications delineated by the green band and DCHM data, the improvements in the overall accuracy compared to the RGB ranged from 5.7% for the RGBS to 9.0% for the RGBIS and from 8.3% for the RGBS to 11.8% for the RGBIS. The laser intensity and slope derived from the ALS data may be valuable sources of information for tree species classification, and in terms of distinguishing species for the detection of individual trees, the findings of this study demonstrate the advantages of using DCHM instead of optical data to delineate tree crowns. In conclusion, the synthesis of individual tree delineation using DCHM data and species classification using the RGBIS combination is recommended for interpreting forest resources in the study area. However, the usefulness of this approach must be verified in future studies through its application to other forests.

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LIDAR-based geometric reconstruction of boreal type forest stands at single tree level for forest and wildland fire management

Cited by 338 publications

References 15 publications

LiDAR derived ecological integrity indicators for riparian zones: Application to the Houille river in Southern Belgium/Northern France

LiDAR derived ecological integrity indicators for riparian zones: Application to the Houille river in Southern Belgium/Northern France

Integration of tree allometry rules to treetops detection and tree crowns delineation using airborne lidar data

Interpretation of Forest Resources at the Individual Tree Level in Japanese Conifer Plantations Using Airborne LiDAR Data

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